Several techniques have been investigated over the years with the goal of helping promote human-computer interactions, particularly to allow users to have more human-like interactions with computers. In the context of verbal or written interaction, one approach is to enable the computer to understand phrases provided in a natural language format as uttered or typed by humans. An important factor in computer understanding then is to ensure the computer can, to a reasonable extent, understand what is being said by the user.
Various attempts at addressing this problem have been considered. For example, conceptual graphs have been employed to capture the meaning and content of a human utterance. Additional information describing various aspects and examples of conceptual graphs, link grammars, and associative databases are described in “PRACTICAL NATURAL LANGUAGE PROCESSING QUESTION ANSWERING USING GRAPHS”, PhD dissertation by Gil Emanuel Fuchs, University of California Santa Cruz, December 2004, which is herein incorporated by reference. However, while conceptual graphs can be powerful constructs for capturing the meaning of language, such graphs must typically be created from natural language using some form of artificial intelligence and/or manual input by a skilled operator. This has generally limited the usage of conceptual graphs in commercial application environments.
As the amount of data stored and accessed by users increases considerably every day, techniques are desired that allow for efficient storage and searching of such data, in a manner that allows for ease of use by the user, and also provides for additional industrial uses. These are some of the areas that embodiments of the present invention are intended to address.